Afforestation is a main tool for preventing desertification and soil erosion in arid and semiarid regions of Iran. Large-scale afforestation, however, has poorly understood consequences for the future ecosystems in the term of ecosystems protection. The objective of the present study is to identify changes in soil properties following different intervals of planting of Ailanthus altissima (tree of heaven) in semiarid afforestation of Iran (Chitgar Forest Park, Tehran). For this purpose, sand, silt and clay ratios, bulk density, soil moisture, pH, electrical conductivity, phosphorus, potassium, magnesium, calcium, sodium, total soil N, and total carbon was measured. Our study highlighted the potential of the invasive trees by A. altissima, to alter soil properties along chronosequence. Almost all soil quality attributes showed a declining trend with stand age. A continuous decline in soil quality indicated that the present land management may not be sustainable. Therefore, an improved management practice is imperative to sustain soil quality and maintain long-term productivity of plantation forests. Thinning activity will be required to reduce the number of trees competing for the same nutrients especially in a older stand to protect forest soils.

The development of flexible, wearable electronic devices is one of the future directions of technology development. Flexible conductive materials are important supporting materials for wearable electronic devices. Polymer has excellent flexibility; it is an important way to prepare flexible conductors from polymer-based conductive composites. In this paper, the research progress of polymer-based flexible conductive composites is summarized in terms of preparation and characterization methods. The key factors to realize flexible conductors are put forward, namely, the maintenance of excellent polymer elasticity and the realization of stability. The design and preparation of the extensible conductor with high-elasticity matrix and nanofiller are introduced in detail, and the problems in the current research are summarized.

To achieve sustainable development, detailed planning, control and management of land cover changes that occur naturally or by human caused artificial factors, are essential. Urban managers and planners need a tool that represents them the information accurate, fast and in exact time. In this study, land use changes of 3 periods, 1994-2002, 2002-2009, 2009-2015 and predictions of 2009, 2015 and 2023 were assessed. In this paper, Maximum Likelihood method was used to classify the images, so that after evaluation of accuracy, amount of overall accuracy for images of 2013 was 85.55% and its Kappa coefficient was 80.03%. To predict land use changes, Markov-CA model was used after assessing the accuracy, and the amount of overall accuracy for 2009 was 82.57% and for 2015 was 93.865%. Then web GIS application was designed via map server application and evoked shape files through map file and open layers to browser environment and for design of appearance of website CSS, HTML and JavaScript languages were used. HTML is  responsible for creating the foundation and overall structure of webpage but beautifying and layout design on CSS. 

In view of the fact that the convolution neural network segmentation method lacks to capture the global dependency of infected areas in COVID-19 images, which is not conducive to the complete segmentation of scattered lesion areas, this paper proposes a COVID-19 lesion segmentation method UniUNet based on UniFormer with its strong ability to capture global dependency. Firstly, a U-shaped encoder-decoder structure based on UniFormer is designed, which can enhance the cooperation ability of local and global relations. Secondly, Swin spatial pyramid pooling module is introduced to compensate the influence of spatial resolution reduction in the encoder process and generate multi-scale representation. Multi-scale attention gate is introduced at the skip connection to suppress redundant features and enhance important features. Experiment results show that, compared with the other four methods, the proposed model achieves better results in Dice, loU and Recall on COVID-19-CT-Seg and CC-CCIII dataset, and achieves a more complete segmentation of the lesion area.

Urbanization plays a crucial role in facilitating the integration of population growth, industrial development, economic expansion, and energy consumption. In this paper, we aim to examine the relationships between CO2 emissions and various factors including economic growth, urbanization, financial development, and energy consumption within Pakistan’s building sector. The study utilizes annual data spanning from 1990 to 2020. To analyze the cointegration relationship between these variables, we employ the quantile autoregressive distributed lag error correction model (QARDL-ECM). The findings of this research provide evidence supporting the presence of an asymmetric and nonlinear long-term relationship between the variables under investigation. Based on these results, we suggest the implementation of tariffs on nonrenewable energy sources and the formulation of policies that promote sustainable energy practices. By doing so, policymakers and architects can effectively contribute to minimising environmental damage. Overall, this study offers valuable insights that can assist policymakers and architects in making informed decisions to mitigate environmental harm while fostering sustainable development.